The PSIIM (Program in Systems Immunology and Infectious Disease Modeling) is now the Laboratory of Systems Biology (LSB). The LSB represents a new multidisciplinary research initiative focused on the immune system, with an emphasis on quantitative, systems-level, microscopic and macroscopic analysis and computer modeling of immune functions, integration of these modeling efforts with data sets derived from global analyses of cell components, and the development and application of advanced imaging methods to the analysis of immune responses in vivo in models systems, and ultimately, man. The program is designed to deal with the existing lack of any large-scale effort to understand the engineering of the immune system from the biochemical through the organismal levels and to generate predictive models based on such understanding. The overall goal of the LSB will be the development of a new level of integrated understanding of how the immune system functions and how it interacts with pathogens. The primary goal is the development of systematic knowledge about cellular, tissue-level, and organismal networks, including but not limited to accumulation of the specific information necessary to devise robust quantitative, predictive models of immune behavior in various circumstances, including exposure to infectious agents, following vaccine administration, or in autoimmune diseases. A key effort will be the implementation of the type of measurement rigor needed for effective modeling at all levels of immune organization, from the biochemical to the whole animal. The Immunology Team of the former PSIIM (now part of the Lymphocyte Biology Section, Laboratory of Systems Biology) has undertaken as a major project a top-down analysis of the immune and non-immune tissue response of mice to various strains of influenza virus. Highly standardized preparations of both mildly pathogenic (Tx91) and highly pathogenic (PR8) viruses have been used at varying infectious doses in a single inbred strain of mouse and several hundred highly qualified microarray transcriptional analyses have been conducted with RNA isolated from infected lung tissues of these mice at varying time points post-inoculation. Tissues from the infected animals have also been subjected to cell recovery and highly multiplexed flow cytometric analysis, along with automated image analysis for tracking of the extent of influenza infection of cells within the lung tissue. These studies revealed markedly enhanced recruitment of myeloid cell subpopulations, especially inflammatory monocytes and neutrophils, in lungs of animals infected with the pathogenic PR8 viruses. We then developed methods for 9+ color flow cytometric separation of hematopoietic cell subsets (lymphoid and myeloid) and non-hematopoietic cells from infected lungs, validated the separation methods as not contributing to substantial changes in RNA patterns, and completed acquisition of microarray data on these purified subpopulations to increase the resolution of the analysis. These data all point to a special role for myeloid cells in the difference pathogenicity of the two primary strains of virus being studied, and these implications are consistent with data obtained with data obtained using a third strain of virus that differs in its HN type but shares core components with the lethal virus and that has an intermediate phenotype. A variety of informatic tools have been employed to organize and analyze the emerging data sets, especially a k-means clustering algorithm that allows study of the RNA response in terms of co-regulated gene sets with linked function (modules). Such modular gene set analysis has uncovered marked differences in transcriptional responses with the PR8 vs. Tx91 strains of virus that can be assigned to specific biological processes. Principal component analysis (PCA) has shown that the transcriptional responses to infection results in cell-type specific changes that largely reflect cell recruitment into the lungs and also context (infection-type) specific changes within the cell-specific gene sets. Furthermore, gene sets related to inflammatory responses are the major component associated with lethality, whereas anti-viral gene sets are similar with both the low and high pathogenicity viruses. A positive feedback pathway involving virus-induced chemokine production that facilitates recruitment of myeloid cells to the lungs that then leads to further recruitment upon exposure to virus was uncovered. Finally, image analysis revealed that the highly pathogenic virus, despite a similar plaque titer to the non-pathogenic strain, spreads more extensively in the large airways and gas exchange components of the lungs. Together, these data suggest that uninterrupted amplification of myeloid cell recruitment and inflammatory cytokine production induced by rapidly spreading virus plays a key role in pathogenic infections. In support of this model, attenuating but not eliminating myeloid cell recruitment using depleting antibodies rescues mice from early lethality of PR8 infection, whereas total depletion accelerates disease due to a lack of basal innate immunity. Thus, this study has uncovered a core feedback circuit involving innate inflammation that drives early lethality in influenza infection and provides new targets for intervention in this disease.